Papers - Pandas Profiling Report

Dataset statistics

Number of variables	16
Number of observations	283004
Missing cells	609
Missing cells (%)	< 0.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	17.4 MiB
Average record size in memory	64.4 B

Variable types

Numeric	9
Categorical	7

Warnings

`SC` has a high cardinality: 2649 distinct values	High cardinality
`Country` has a high cardinality: 177 distinct values	High cardinality
`CountryCode` has a high cardinality: 177 distinct values	High cardinality
`ArtsHumanities` is highly skewed (γ1 = 42.58223174)	Skewed
`TCperYear` is highly skewed (γ1 = 89.11640174)	Skewed
`NumAuthors` is highly skewed (γ1 = 21.01065718)	Skewed
`ArtsHumanities` has 282765 (99.9%) zeros	Zeros
`LifeSciencesBiomedicine` has 238163 (84.2%) zeros	Zeros
`PhysicalSciences` has 219268 (77.5%) zeros	Zeros
`SocialSciences` has 274870 (97.1%) zeros	Zeros
`Technology` has 54286 (19.2%) zeros	Zeros
`TCperYear` has 77342 (27.3%) zeros	Zeros

Reproduction

Analysis started	2021-01-11 16:15:51.477294
Analysis finished	2021-01-11 16:16:32.123145
Duration	40.65 seconds
Software version	pandas-profiling v2.10.0
Download configuration	config.yaml

PY
Real number (ℝ_≥0)

Distinct	29
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2010.61726
Minimum	1990
Maximum	2018
Zeros	0
Zeros (%)	0.0%
Memory size	552.9 KiB

Quantile statistics

Minimum	1990
5-th percentile	1999
Q1	2006
median	2012
Q3	2016
95-th percentile	2018
Maximum	2018
Range	28
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	6.263750677
Coefficient of variation (CV)	0.003115337166
Kurtosis	-0.3732993416
Mean	2010.61726
Median Absolute Deviation (MAD)	5
Skewness	-0.7143466555
Sum	569012727
Variance	39.23457254
Monotocity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
2018	33291	11.8%
2017	28162	10.0%
2016	21970	7.8%
2015	19805	7.0%
2014	16800	5.9%
2013	14872	5.3%
2012	13761	4.9%
2009	13662	4.8%
2008	12614	4.5%
2011	12035	4.3%
Other values (19)	96032	33.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1990	72	< 0.1%
1991	390	0.1%
1992	674	0.2%
1993	834	0.3%
1994	994	0.4%

Value	Count	Frequency (%)
2018	33291	11.8%
2017	28162	10.0%
2016	21970	7.8%
2015	19805	7.0%
2014	16800	5.9%

SC
Categorical

HIGH CARDINALITY

Distinct	2649
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Memory size	653.6 KiB

Computer Science	43160
Computer Science; Engineering	25349
Engineering	20686
Physics	5580
Automation & Control Systems; Engineering	5568
Other values (2644)	182661

Length

Max length	188
Median length	29
Mean length	33.81959972
Min length	3

Characters and Unicode

Total characters	9571082
Distinct characters	49
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	592 ?
Unique (%)	0.2%

Sample

1st row	Computer Science; Engineering
2nd row	Computer Science; Engineering
3rd row	Computer Science; Engineering
4th row	Computer Science; Engineering
5th row	Computer Science; Engineering

Value	Count	Frequency (%)
Computer Science	43160	15.3%
Computer Science; Engineering	25349	9.0%
Engineering	20686	7.3%
Physics	5580	2.0%
Automation & Control Systems; Engineering	5568	2.0%
Computer Science; Neurosciences & Neurology	4586	1.6%
Science & Technology - Other Topics	4464	1.6%
Computer Science; Engineering; Telecommunications	3972	1.4%
Automation & Control Systems; Computer Science	3919	1.4%
Mathematics	3864	1.4%
Other values (2639)	161856	57.2%

Histogram of lengths of the category

Value	Count	Frequency (%)
science	166765	15.2%
	149290	13.6%
computer	120642	11.0%
engineering	119602	10.9%
technology	27923	2.5%
systems	25785	2.3%
control	25785	2.3%
automation	25785	2.3%
sciences	15705	1.4%
physics	15381	1.4%
Other values (201)	405750	36.9%

Most occurring characters

Value	Count	Frequency (%)
e	1129281	11.8%
n	861036	9.0%
	815409	8.5%
i	758086	7.9%
c	642036	6.7%
o	610192	6.4%
t	500855	5.2%
r	485700	5.1%
g	403263	4.2%
s	353199	3.7%
Other values (39)	3012025	31.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	7417224	77.5%
Uppercase Letter	949152	9.9%
Space Separator	815409	8.5%
Other Punctuation	377503	3.9%
Dash Punctuation	11794	0.1%

Most frequent character per category

Value	Count	Frequency (%)
e	1129281	15.2%
n	861036	11.6%
i	758086	10.2%
c	642036	8.7%
o	610192	8.2%
t	500855	6.8%
r	485700	6.5%
g	403263	5.4%
s	353199	4.8%
m	328455	4.4%
Other values (13)	1345121	18.1%

Value	Count	Frequency (%)
S	219962	23.2%
C	167753	17.7%
E	158137	16.7%
M	69861	7.4%
T	59433	6.3%
A	44479	4.7%
P	39813	4.2%
I	39020	4.1%
R	34894	3.7%
O	29973	3.2%
Other values (11)	85827	9.0%

Value	Count	Frequency (%)
;	236197	62.6%
&	137589	36.4%
,	3717	1.0%

Value	Count	Frequency (%)
	815409	100.0%

Value	Count	Frequency (%)
-	11794	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	8366376	87.4%
Common	1204706	12.6%

Most frequent character per script

Value	Count	Frequency (%)
e	1129281	13.5%
n	861036	10.3%
i	758086	9.1%
c	642036	7.7%
o	610192	7.3%
t	500855	6.0%
r	485700	5.8%
g	403263	4.8%
s	353199	4.2%
m	328455	3.9%
Other values (34)	2294273	27.4%

Value	Count	Frequency (%)
	815409	67.7%
;	236197	19.6%
&	137589	11.4%
-	11794	1.0%
,	3717	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	9571082	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	1129281	11.8%
n	861036	9.0%
	815409	8.5%
i	758086	7.9%
c	642036	6.7%
o	610192	6.4%
t	500855	5.2%
r	485700	5.1%
g	403263	4.2%
s	353199	3.7%
Other values (39)	3012025	31.5%

ArtsHumanities
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	8
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.0005465428387
Minimum	0
Maximum	1
Zeros	282765
Zeros (%)	99.9%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	1
Range	1
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.02078563022
Coefficient of variation (CV)	38.0311089
Kurtosis	1923.509438
Mean	0.0005465428387
Median Absolute Deviation (MAD)	0
Skewness	42.58223174
Sum	154.6738095
Variance	0.0004320424236
Monotocity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
0	282765	99.9%
1	96	< 0.1%
0.5	91	< 0.1%
0.3333333333	20	< 0.1%
0.25	13	< 0.1%
0.2	7	< 0.1%
0.1666666667	6	< 0.1%
0.1428571429	6	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	282765	99.9%
0.1428571429	6	< 0.1%
0.1666666667	6	< 0.1%
0.2	7	< 0.1%
0.25	13	< 0.1%

Value	Count	Frequency (%)
1	96	< 0.1%
0.5	91	< 0.1%
0.3333333333	20	< 0.1%
0.25	13	< 0.1%
0.2	7	< 0.1%

LifeSciencesBiomedicine
Real number (ℝ_≥0)

ZEROS

Distinct	15
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.1112536129
Minimum	0
Maximum	1
Zeros	238163
Zeros (%)	84.2%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	1
Range	1
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.2803793536
Coefficient of variation (CV)	2.520182008
Kurtosis	4.616926168
Mean	0.1112536129
Median Absolute Deviation (MAD)	0
Skewness	2.452339835
Sum	31485.21746
Variance	0.07861258191
Monotocity	Not monotonic

Histogram with fixed size bins (bins=15)

Value	Count	Frequency (%)
0	238163	84.2%
1	20311	7.2%
0.5	12289	4.3%
0.3333333333	7337	2.6%
0.6666666667	2388	0.8%
0.25	1300	0.5%
0.6	698	0.2%
0.75	126	< 0.1%
0.2	111	< 0.1%
0.1666666667	83	< 0.1%
Other values (5)	198	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	238163	84.2%
0.1111111111	2	< 0.1%
0.1666666667	83	< 0.1%
0.2	111	< 0.1%
0.25	1300	0.5%

Value	Count	Frequency (%)
1	20311	7.2%
0.8333333333	74	< 0.1%
0.8	23	< 0.1%
0.75	126	< 0.1%
0.6666666667	2388	0.8%

PhysicalSciences
Real number (ℝ_≥0)

ZEROS

Distinct	16
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.1502119242
Minimum	0
Maximum	1
Zeros	219268
Zeros (%)	77.5%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	1
Range	1
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.3103166229
Coefficient of variation (CV)	2.065858783
Kurtosis	2.320862641
Mean	0.1502119242
Median Absolute Deviation (MAD)	0
Skewness	1.934476673
Sum	42510.5754
Variance	0.09629640644
Monotocity	Not monotonic

Histogram with fixed size bins (bins=16)

Value	Count	Frequency (%)
0	219268	77.5%
1	25257	8.9%
0.5	17552	6.2%
0.3333333333	10461	3.7%
0.6666666667	5227	1.8%
0.25	3229	1.1%
0.2	866	0.3%
0.4	791	0.3%
0.75	178	0.1%
0.6	68	< 0.1%
Other values (6)	107	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	219268	77.5%
0.1428571429	40	< 0.1%
0.1666666667	36	< 0.1%
0.2	866	0.3%
0.2222222222	2	< 0.1%

Value	Count	Frequency (%)
1	25257	8.9%
0.8	27	< 0.1%
0.75	178	0.1%
0.6666666667	5227	1.8%
0.6	68	< 0.1%

SocialSciences
Real number (ℝ_≥0)

ZEROS

Distinct	14
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.02000337703
Minimum	0
Maximum	1
Zeros	274870
Zeros (%)	97.1%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	1
Range	1
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.126590409
Coefficient of variation (CV)	6.32845188
Kurtosis	47.35204179
Mean	0.02000337703
Median Absolute Deviation (MAD)	0
Skewness	6.834607574
Sum	5661.035714
Variance	0.01602513165
Monotocity	Not monotonic

Histogram with fixed size bins (bins=14)

Value	Count	Frequency (%)
0	274870	97.1%
1	3748	1.3%
0.5	2258	0.8%
0.3333333333	1045	0.4%
0.25	616	0.2%
0.6666666667	333	0.1%
0.2	38	< 0.1%
0.75	29	< 0.1%
0.6	28	< 0.1%
0.4	22	< 0.1%
Other values (4)	17	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	274870	97.1%
0.1428571429	1	< 0.1%
0.1666666667	10	< 0.1%
0.2	38	< 0.1%
0.25	616	0.2%

Value	Count	Frequency (%)
1	3748	1.3%
0.8	1	< 0.1%
0.75	29	< 0.1%
0.6666666667	333	0.1%
0.6	28	< 0.1%

Technology
Real number (ℝ_≥0)

ZEROS

Distinct	18
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.717984543
Minimum	0
Maximum	1
Zeros	54286
Zeros (%)	19.2%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0.5
median	1
Q3	1
95-th percentile	1
Maximum	1
Range	1
Interquartile range (IQR)	0.5

Descriptive statistics

Standard deviation	0.3980375418
Coefficient of variation (CV)	0.55438177
Kurtosis	-0.766263932
Mean	0.717984543
Median Absolute Deviation (MAD)	0
Skewness	-0.958126331
Sum	203192.4976
Variance	0.1584338847
Monotocity	Not monotonic

Histogram with fixed size bins (bins=18)

Value	Count	Frequency (%)
1	175142	61.9%
0	54286	19.2%
0.5	27217	9.6%
0.6666666667	12241	4.3%
0.3333333333	7960	2.8%
0.75	3376	1.2%
0.6	780	0.3%
0.25	765	0.3%
0.2	729	0.3%
0.8	179	0.1%
Other values (8)	329	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	54286	19.2%
0.1428571429	1	< 0.1%
0.1666666667	74	< 0.1%
0.2	729	0.3%
0.25	765	0.3%

Value	Count	Frequency (%)
1	175142	61.9%
0.8571428571	40	< 0.1%
0.8333333333	21	< 0.1%
0.8	179	0.1%
0.75	3376	1.2%

ComputerScience
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.2 MiB

0	162362
1	120642

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	283004
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Value	Count	Frequency (%)
0	162362	57.4%
1	120642	42.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	162362	57.4%
1	120642	42.6%

Most occurring characters

Value	Count	Frequency (%)
0	162362	57.4%
1	120642	42.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	283004	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	162362	57.4%
1	120642	42.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	283004	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	162362	57.4%
1	120642	42.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	283004	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	162362	57.4%
1	120642	42.6%

Health
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.2 MiB

0	252025
1	30979

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	283004
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Value	Count	Frequency (%)
0	252025	89.1%
1	30979	10.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	252025	89.1%
1	30979	10.9%

Most occurring characters

Value	Count	Frequency (%)
0	252025	89.1%
1	30979	10.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	283004	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	252025	89.1%
1	30979	10.9%

Most occurring scripts

Value	Count	Frequency (%)
Common	283004	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	252025	89.1%
1	30979	10.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	283004	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	252025	89.1%
1	30979	10.9%

NR
Real number (ℝ_≥0)

Distinct	402
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	30.45958361
Minimum	1
Maximum	1972
Zeros	0
Zeros (%)	0.0%
Memory size	552.9 KiB

Quantile statistics

Minimum	1
5-th percentile	7
Q1	14
median	24
Q3	39
95-th percentile	72
Maximum	1972
Range	1971
Interquartile range (IQR)	25

Descriptive statistics

Standard deviation	27.88476565
Coefficient of variation (CV)	0.9154677231
Kurtosis	233.3866771
Mean	30.45958361
Median Absolute Deviation (MAD)	11
Skewness	7.500231363
Sum	8620184
Variance	777.5601556
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
12	8112	2.9%
15	8110	2.9%
10	7872	2.8%
16	7780	2.7%
14	7747	2.7%
11	7705	2.7%
13	7552	2.7%
18	7341	2.6%
20	7321	2.6%
17	7296	2.6%
Other values (392)	206168	72.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	247	0.1%
2	657	0.2%
3	1481	0.5%
4	2591	0.9%
5	4005	1.4%

Value	Count	Frequency (%)
1972	2	< 0.1%
1073	1	< 0.1%
882	1	< 0.1%
863	3	< 0.1%
770	1	< 0.1%

TCperYear
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	3692
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1.789662283
Minimum	0
Maximum	1587.8
Zeros	77342
Zeros (%)	27.3%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0.5
Q3	1.692307692
95-th percentile	7
Maximum	1587.8
Range	1587.8
Interquartile range (IQR)	1.692307692

Descriptive statistics

Standard deviation	7.703522293
Coefficient of variation (CV)	4.304455854
Kurtosis	14867.77821
Mean	1.789662283
Median Absolute Deviation (MAD)	0.5
Skewness	89.11640174
Sum	506481.5848
Variance	59.34425572
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	77342	27.3%
0.5	10805	3.8%
1	10486	3.7%
0.3333333333	7399	2.6%
0.25	5098	1.8%
2	4904	1.7%
0.6666666667	4689	1.7%
1.5	4021	1.4%
0.2	3696	1.3%
0.1666666667	2932	1.0%
Other values (3682)	151632	53.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	77342	27.3%
0.03333333333	6	< 0.1%
0.03448275862	27	< 0.1%
0.03571428571	31	< 0.1%
0.03703703704	50	< 0.1%

Value	Count	Frequency (%)
1587.8	2	< 0.1%
932.6	1	< 0.1%
853.5	1	< 0.1%
746	1	< 0.1%
558.6	1	< 0.1%

NumAuthors
Real number (ℝ_≥0)

SKEWED

Distinct	134
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	10.71077794
Minimum	0
Maximum	3049
Zeros	1
Zeros (%)	< 0.1%
Memory size	552.9 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	2
median	3
Q3	4
95-th percentile	7
Maximum	3049
Range	3049
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	125.4928861
Coefficient of variation (CV)	11.71650526
Kurtosis	460.1208039
Mean	10.71077794
Median Absolute Deviation (MAD)	1
Skewness	21.01065718
Sum	3031193
Variance	15748.46446
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3	74730	26.4%
2	65484	23.1%
4	55815	19.7%
5	31740	11.2%
1	18915	6.7%
6	16026	5.7%
7	7733	2.7%
8	4015	1.4%
9	2226	0.8%
10	1352	0.5%
Other values (124)	4968	1.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	18915	6.7%
2	65484	23.1%
3	74730	26.4%
4	55815	19.7%

Value	Count	Frequency (%)
3049	39	< 0.1%
3041	39	< 0.1%
2908	41	< 0.1%
2900	42	< 0.1%
2888	41	< 0.1%

Organisation
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	276.6 KiB

Academia	272295
Company	10709

Length

Max length	8
Median length	8
Mean length	7.962159545
Min length	7

Characters and Unicode

Total characters	2253323
Distinct characters	12
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Academia
2nd row	Company
3rd row	Academia
4th row	Academia
5th row	Academia

Value	Count	Frequency (%)
Academia	272295	96.2%
Company	10709	3.8%

Histogram of lengths of the category

Value	Count	Frequency (%)
academia	272295	96.2%
company	10709	3.8%

Most occurring characters

Value	Count	Frequency (%)
a	555299	24.6%
m	283004	12.6%
A	272295	12.1%
c	272295	12.1%
d	272295	12.1%
e	272295	12.1%
i	272295	12.1%
C	10709	0.5%
o	10709	0.5%
p	10709	0.5%
Other values (2)	21418	1.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1970319	87.4%
Uppercase Letter	283004	12.6%

Most frequent character per category

Value	Count	Frequency (%)
a	555299	28.2%
m	283004	14.4%
c	272295	13.8%
d	272295	13.8%
e	272295	13.8%
i	272295	13.8%
o	10709	0.5%
p	10709	0.5%
n	10709	0.5%
y	10709	0.5%

Value	Count	Frequency (%)
A	272295	96.2%
C	10709	3.8%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2253323	100.0%

Most frequent character per script

Value	Count	Frequency (%)
a	555299	24.6%
m	283004	12.6%
A	272295	12.1%
c	272295	12.1%
d	272295	12.1%
e	272295	12.1%
i	272295	12.1%
C	10709	0.5%
o	10709	0.5%
p	10709	0.5%
Other values (2)	21418	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2253323	100.0%

Most frequent character per block

Value	Count	Frequency (%)
a	555299	24.6%
m	283004	12.6%
A	272295	12.1%
c	272295	12.1%
d	272295	12.1%
e	272295	12.1%
i	272295	12.1%
C	10709	0.5%
o	10709	0.5%
p	10709	0.5%
Other values (2)	21418	1.0%

Region
Categorical

Distinct	9
Distinct (%)	< 0.1%
Missing	605
Missing (%)	0.2%
Memory size	276.9 KiB

NorthEast Asia	83987
Western Europe	63736
North America	47064
Eastern Europe to Central Asia	21829
MiddleEast and North Africa	19708
Other values (4)	46075

Length

Max length	30
Median length	14
Mean length	17.04277636
Min length	10

Characters and Unicode

Total characters	4812863
Distinct characters	27
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	North America
2nd row	SouthEast Asia and Pacific
3rd row	Western Europe
4th row	Western Europe
5th row	North America

Value	Count	Frequency (%)
NorthEast Asia	83987	29.7%
Western Europe	63736	22.5%
North America	47064	16.6%
Eastern Europe to Central Asia	21829	7.7%
MiddleEast and North Africa	19708	7.0%
SouthEast Asia and Pacific	18570	6.6%
South Asia	15461	5.5%
Latin America and Caribbean	10189	3.6%
Sub Saharan Africa	1855	0.7%
(Missing)	605	0.2%

Histogram of lengths of the category

Value	Count	Frequency (%)
asia	139847	19.2%
europe	85565	11.7%
northeast	83987	11.5%
north	66772	9.2%
western	63736	8.7%
america	57253	7.9%
and	48467	6.6%
central	21829	3.0%
to	21829	3.0%
eastern	21829	3.0%
Other values (9)	117960	16.2%

Most occurring characters

Value	Count	Frequency (%)
a	487755	10.1%
	446675	9.3%
t	446467	9.3%
r	434578	9.0%
s	347677	7.2%
e	343845	7.1%
i	295889	6.1%
o	292184	6.1%
E	229659	4.8%
A	218663	4.5%
Other values (17)	1269471	26.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3585145	74.5%
Uppercase Letter	781043	16.2%
Space Separator	446675	9.3%

Most frequent character per category

Value	Count	Frequency (%)
a	487755	13.6%
t	446467	12.5%
r	434578	12.1%
s	347677	9.7%
e	343845	9.6%
i	295889	8.3%
o	292184	8.1%
h	186645	5.2%
n	178094	5.0%
u	121451	3.4%
Other values (7)	450560	12.6%

Value	Count	Frequency (%)
E	229659	29.4%
A	218663	28.0%
N	150759	19.3%
W	63736	8.2%
S	37741	4.8%
C	32018	4.1%
M	19708	2.5%
P	18570	2.4%
L	10189	1.3%

Value	Count	Frequency (%)
	446675	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4366188	90.7%
Common	446675	9.3%

Most frequent character per script

Value	Count	Frequency (%)
a	487755	11.2%
t	446467	10.2%
r	434578	10.0%
s	347677	8.0%
e	343845	7.9%
i	295889	6.8%
o	292184	6.7%
E	229659	5.3%
A	218663	5.0%
h	186645	4.3%
Other values (16)	1082826	24.8%

Value	Count	Frequency (%)
	446675	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4812863	100.0%

Most frequent character per block

Value	Count	Frequency (%)
a	487755	10.1%
	446675	9.3%
t	446467	9.3%
r	434578	9.0%
s	347677	7.2%
e	343845	7.1%
i	295889	6.1%
o	292184	6.1%
E	229659	4.8%
A	218663	4.5%
Other values (17)	1269471	26.4%

Country
Categorical

HIGH CARDINALITY

Distinct	177
Distinct (%)	0.1%
Missing	2
Missing (%)	< 0.1%
Memory size	559.2 KiB

China	56485
USA	38625
India	13792
United Kingdom	13719
Japan	11061
Other values (172)	149320

Length

Max length	38
Median length	6
Mean length	7.204942015
Min length	3

Characters and Unicode

Total characters	2039013
Distinct characters	54
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	18 ?
Unique (%)	< 0.1%

Sample

1st row	USA
2nd row	Australia
3rd row	Belgium
4th row	France
5th row	USA

Value	Count	Frequency (%)
China	56485	20.0%
USA	38625	13.6%
India	13792	4.9%
United Kingdom	13719	4.8%
Japan	11061	3.9%
Iran, Islamic Republic of	10407	3.7%
Canada	8589	3.0%
Taiwan	8443	3.0%
Germany	8381	3.0%
Italy	8318	2.9%
Other values (167)	105182	37.2%

Histogram of lengths of the category

Value	Count	Frequency (%)
china	56485	16.1%
usa	38625	11.0%
republic	19853	5.6%
of	18235	5.2%
united	14297	4.1%
india	13792	3.9%
kingdom	13719	3.9%
japan	11061	3.1%
islamic	10407	3.0%
iran	10407	3.0%
Other values (194)	144923	41.2%

Most occurring characters

Value	Count	Frequency (%)
a	285136	14.0%
i	198900	9.8%
n	193990	9.5%
e	106893	5.2%
r	81634	4.0%
l	77720	3.8%
d	69429	3.4%
C	69083	3.4%
	68802	3.4%
h	64969	3.2%
Other values (44)	822457	40.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1541367	75.6%
Uppercase Letter	410582	20.1%
Space Separator	68802	3.4%
Other Punctuation	18261	0.9%
Dash Punctuation	1	< 0.1%

Most frequent character per category

Value	Count	Frequency (%)
a	285136	18.5%
i	198900	12.9%
n	193990	12.6%
e	106893	6.9%
r	81634	5.3%
l	77720	5.0%
d	69429	4.5%
h	64969	4.2%
o	63758	4.1%
u	47393	3.1%
Other values (16)	351545	22.8%

Value	Count	Frequency (%)
C	69083	16.8%
S	59094	14.4%
U	53661	13.1%
A	51318	12.5%
I	46281	11.3%
R	24179	5.9%
K	22107	5.4%
T	17253	4.2%
J	11494	2.8%
G	11474	2.8%
Other values (14)	44638	10.9%

Value	Count	Frequency (%)
,	18235	99.9%
'	26	0.1%

Value	Count	Frequency (%)
	68802	100.0%

Value	Count	Frequency (%)
-	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1951949	95.7%
Common	87064	4.3%

Most frequent character per script

Value	Count	Frequency (%)
a	285136	14.6%
i	198900	10.2%
n	193990	9.9%
e	106893	5.5%
r	81634	4.2%
l	77720	4.0%
d	69429	3.6%
C	69083	3.5%
h	64969	3.3%
o	63758	3.3%
Other values (40)	740437	37.9%

Value	Count	Frequency (%)
	68802	79.0%
,	18235	20.9%
'	26	< 0.1%
-	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2039013	100.0%

Most frequent character per block

Value	Count	Frequency (%)
a	285136	14.0%
i	198900	9.8%
n	193990	9.5%
e	106893	5.2%
r	81634	4.0%
l	77720	3.8%
d	69429	3.4%
C	69083	3.4%
	68802	3.4%
h	64969	3.2%
Other values (44)	822457	40.3%

CountryCode
Categorical

HIGH CARDINALITY

Distinct	177
Distinct (%)	0.1%
Missing	2
Missing (%)	< 0.1%
Memory size	559.2 KiB

CHN	56485
USA	38625
IND	13792
GBR	13719
JPN	11061
Other values (172)	149320

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	849006
Distinct characters	26
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	18 ?
Unique (%)	< 0.1%

Sample

1st row	USA
2nd row	AUS
3rd row	BEL
4th row	FRA
5th row	USA

Value	Count	Frequency (%)
CHN	56485	20.0%
USA	38625	13.6%
IND	13792	4.9%
GBR	13719	4.8%
JPN	11061	3.9%
IRN	10407	3.7%
CAN	8589	3.0%
TWN	8443	3.0%
DEU	8381	3.0%
ITA	8318	2.9%
Other values (167)	105182	37.2%

Histogram of lengths of the category

Value	Count	Frequency (%)
chn	56485	20.0%
usa	38625	13.6%
ind	13792	4.9%
gbr	13719	4.8%
jpn	11061	3.9%
irn	10407	3.7%
can	8589	3.0%
twn	8443	3.0%
deu	8381	3.0%
ita	8318	2.9%
Other values (167)	105182	37.2%

Most occurring characters

Value	Count	Frequency (%)
N	120288	14.2%
A	83882	9.9%
C	73916	8.7%
S	70396	8.3%
U	70343	8.3%
R	67542	8.0%
H	62773	7.4%
I	37542	4.4%
P	30384	3.6%
T	29923	3.5%
Other values (16)	202017	23.8%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	849006	100.0%

Most frequent character per category

Value	Count	Frequency (%)
N	120288	14.2%
A	83882	9.9%
C	73916	8.7%
S	70396	8.3%
U	70343	8.3%
R	67542	8.0%
H	62773	7.4%
I	37542	4.4%
P	30384	3.6%
T	29923	3.5%
Other values (16)	202017	23.8%

Most occurring scripts

Value	Count	Frequency (%)
Latin	849006	100.0%

Most frequent character per script

Value	Count	Frequency (%)
N	120288	14.2%
A	83882	9.9%
C	73916	8.7%
S	70396	8.3%
U	70343	8.3%
R	67542	8.0%
H	62773	7.4%
I	37542	4.4%
P	30384	3.6%
T	29923	3.5%
Other values (16)	202017	23.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	849006	100.0%

Most frequent character per block

Value	Count	Frequency (%)
N	120288	14.2%
A	83882	9.9%
C	73916	8.7%
S	70396	8.3%
U	70343	8.3%
R	67542	8.0%
H	62773	7.4%
I	37542	4.4%
P	30384	3.6%
T	29923	3.5%
Other values (16)	202017	23.8%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	PY	SC	Technology	ComputerScience	NR	TCperYear	NumAuthors	Organisation	Region	Country	CountryCode
0	1998	Computer Science; Engineering	1.0	1	13	0.545455	3	Academia	North America	USA	USA
1	1998	Computer Science; Engineering	1.0	1	24	0.363636	2	Company	SouthEast Asia and Pacific	Australia	AUS
2	1998	Computer Science; Engineering	1.0	1	13	3.454545	4	Academia	Western Europe	Belgium	BEL
3	1998	Computer Science; Engineering	1.0	1	13	3.454545	4	Academia	Western Europe	France	FRA
4	1998	Computer Science; Engineering	1.0	1	12	0.136364	2	Academia	North America	USA	USA
5	1998	Computer Science; Engineering	1.0	1	19	1.772727	2	Company	South Asia	India	IND
6	1998	Computer Science; Engineering	1.0	1	34	1.181818	2	Academia	North America	USA	USA
7	1998	Computer Science; Engineering	1.0	1	23	0.181818	3	Academia	Western Europe	United Kingdom	GBR
8	1998	Computer Science; Engineering	1.0	1	14	3.136364	3	Company	Western Europe	Germany	DEU
9	1998	Computer Science; Engineering	1.0	1	17	0.409091	3	Academia	North America	USA	USA

Last rows

	PY	SC	ArtsHumanities	LifeSciencesBiomedicine	SocialSciences	Health	NR	TCperYear	NumAuthors	Organisation	Region	Country	CountryCode
282994	2017	General & Internal Medicine	0.0	1.0	0.0	1	21	0.666667	2	Academia	Western Europe	United Kingdom	GBR
282995	2018	Business & Economics; Biomedical Social Sciences	0.0	0.0	1.0	0	3	0.000000	1	Academia	NorthEast Asia	China	CHN
282996	2016	Cultural Studies	0.0	0.0	1.0	0	32	0.000000	1	Academia	SouthEast Asia and Pacific	Australia	AUS
282997	2018	History	1.0	0.0	0.0	0	66	0.000000	1	Academia	Western Europe	Netherlands	NLD
282998	2015	Business & Economics	0.0	0.0	1.0	0	53	0.200000	1	Academia	Western Europe	United Kingdom	GBR
282999	2015	Business & Economics	0.0	0.0	1.0	0	33	0.200000	2	Academia	North America	Canada	CAN
283000	2009	Business & Economics	0.0	0.0	1.0	0	60	0.000000	2	Academia	North America	USA	USA
283001	2001	Literature	1.0	0.0	0.0	0	22	2.368421	2	Academia	North America	USA	USA
283002	2018	Literature	1.0	0.0	0.0	0	34	0.000000	1	Academia	Western Europe	Switzerland	CHE
283003	2017	Literature	1.0	0.0	0.0	0	45	0.000000	1	Academia	Western Europe	United Kingdom	GBR

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows